메뉴 건너뛰기




Volumn 20, Issue 3, 2007, Pages 203-222

Part 1. Automated change detection and characterization in serial MR studies of brain-tumor patients

Author keywords

Brain tumor; Change detection; Serial imaging

Indexed keywords

AUTOMATED CHANGE DETECTION; BRAIN TUMOR; SERIAL IMAGING;

EID: 35648990107     PISSN: 08971889     EISSN: 1618727X     Source Type: Journal    
DOI: 10.1007/s10278-006-1038-1     Document Type: Article
Times cited : (25)

References (39)
  • 2
  • 3
    • 15044355781 scopus 로고    scopus 로고
    • A review of the automated detection of change in serial imaging studies of the brain
    • J Patriarche B Erickson 2004 A review of the automated detection of change in serial imaging studies of the brain J Digit Imaging 17 158 174
    • (2004) J Digit Imaging , vol.17 , pp. 158-174
    • Patriarche, J.1    Erickson, B.2
  • 6
    • 0027076295 scopus 로고
    • Southwest oncology group standard response criteria, endpoint definitions and toxicity criteria
    • S Green G Weiss 1992 Southwest oncology group standard response criteria, endpoint definitions and toxicity criteria Invest New Drugs 10 239 253
    • (1992) Invest New Drugs , vol.10 , pp. 239-253
    • Green, S.1    Weiss, G.2
  • 7
    • 0035202667 scopus 로고    scopus 로고
    • The RECIST (Response Evaluation Criteria in Solid Tumors) criteria: Implications for diagnostic radiologists
    • L Ollivier AR Padhani 2001 The RECIST (Response Evaluation Criteria in Solid Tumors) criteria: implications for diagnostic radiologists Br J Radiol 74 983 986
    • (2001) Br J Radiol , vol.74 , pp. 983-986
    • Ollivier, L.1    Padhani, A.R.2
  • 8
    • 0034594626 scopus 로고    scopus 로고
    • Will there be resistance to the RECIST (Response Evaluation Criteria in Solid Tumors)?
    • EA Gehan MC Tefft 2000 Will there be resistance to the RECIST (Response Evaluation Criteria in Solid Tumors)? J Natl Cancer Inst 92 179 181
    • (2000) J Natl Cancer Inst , vol.92 , pp. 179-181
    • Gehan, E.A.1    Tefft, M.C.2
  • 10
    • 0034963267 scopus 로고    scopus 로고
    • Response evaluation criteria in solid tumors (RECIST): New guidelines
    • Y Tsuchida P Therasse 2001 Response evaluation criteria in solid tumors (RECIST): new guidelines Med Pediatr Oncol 37 1 3
    • (2001) Med Pediatr Oncol , vol.37 , pp. 1-3
    • Tsuchida, Y.1    Therasse, P.2
  • 11
    • 0033709541 scopus 로고    scopus 로고
    • Are current tumour response criteria relevant for the 21st century?
    • AR Padhani JE Husband 2000 Are current tumour response criteria relevant for the 21st century? Br J Radiol 73 1031 1033
    • (2000) Br J Radiol , vol.73 , pp. 1031-1033
    • Padhani, A.R.1    Husband, J.E.2
  • 15
    • 0036624489 scopus 로고    scopus 로고
    • Automatic detection and segmentation of evolving processes in 3D medical images: Application to multiple sclerosis
    • D Rey G Subsol H Delingette N Ayache 2002 Automatic detection and segmentation of evolving processes in 3D medical images: Application to multiple sclerosis Med Image Anal 6 163 179
    • (2002) Med Image Anal , vol.6 , pp. 163-179
    • Rey, D.1    Subsol, G.2    Delingette, H.3    Ayache, N.4
  • 16
    • 0034624843 scopus 로고    scopus 로고
    • Growth patterns in the developing brain detected by using continuum mechanical tensor maps
    • PM Thompson JN Giedd RP Woods D MacDonald AC Evans AW Toga 2000 Growth patterns in the developing brain detected by using continuum mechanical tensor maps Nature 404 190 193
    • (2000) Nature , vol.404 , pp. 190-193
    • Thompson, P.M.1    Giedd, J.N.2    Woods, R.P.3    MacDonald, D.4    Evans, A.C.5    Toga, A.W.6
  • 17
    • 0031694255 scopus 로고    scopus 로고
    • Modeling brain deformations in Alzheimer disease by fluid registration of serial 3D MR images
    • PA Freeborough NC Fox 1998 Modeling brain deformations in Alzheimer disease by fluid registration of serial 3D MR images J Comput Assist Tomogr 22 838 843
    • (1998) J Comput Assist Tomogr , vol.22 , pp. 838-843
    • Freeborough, P.A.1    Fox, N.C.2
  • 18
    • 0032588596 scopus 로고    scopus 로고
    • Deformation analysis to detect and quantify active lesions in three-dimensional medical image sequences
    • JP Thirion G Calmon 1999 Deformation analysis to detect and quantify active lesions in three-dimensional medical image sequences IEEE Trans Med Imag 18 429 441
    • (1999) IEEE Trans Med Imag , vol.18 , pp. 429-441
    • Thirion, J.P.1    Calmon, G.2
  • 20
    • 0142106286 scopus 로고    scopus 로고
    • Time-series analysis of MRI intensity patterns in multiple sclerosis
    • DS Meier CR Guttmann 2003 Time-series analysis of MRI intensity patterns in multiple sclerosis Neuroimage 20 1193 1209
    • (2003) Neuroimage , vol.20 , pp. 1193-1209
    • Meier, D.S.1    Guttmann, C.R.2
  • 21
    • 0031987382 scopus 로고    scopus 로고
    • A nonparametric method for automatic correction of intensity nonuniformity in MRI data
    • JG Sled AP Zijdenbos AC Evans 1998 A nonparametric method for automatic correction of intensity nonuniformity in MRI data IEEE Trans Med Imag 17 87 97
    • (1998) IEEE Trans Med Imag , vol.17 , pp. 87-97
    • Sled, J.G.1    Zijdenbos, A.P.2    Evans, A.C.3
  • 22
    • 84864176887 scopus 로고    scopus 로고
    • National Library of Medicine Bethesda, MD.
    • National Library of Medicine Bethesda, MD. http://www.itk.org
  • 23
    • 84864176182 scopus 로고    scopus 로고
    • Rochester, MN.
    • Mayo Clinic (2005) Rochester, MN. http://www.mayo.edu/bir/software/ Analyze/Analyze1NEW.html
    • (2005)
  • 24
  • 26
    • 0026923824 scopus 로고
    • A comparative analysis of several transformations for enhancement and segmentation of magnetic resonance image scene sequences
    • H Soltanian-Zadeh J Windham D Peck A Yagle 1992 A comparative analysis of several transformations for enhancement and segmentation of magnetic resonance image scene sequences IEEE Trans Med Imag 11 302 318
    • (1992) IEEE Trans Med Imag , vol.11 , pp. 302-318
    • Soltanian-Zadeh, H.1    Windham, J.2    Peck, D.3    Yagle, A.4
  • 29
    • 0033701103 scopus 로고    scopus 로고
    • Partial volume estimation: An improvement for eigenimage method
    • M Siadat H Soltanian-Zadeh 2000 Partial volume estimation: an improvement for eigenimage method SPIE Med Imag 3979 646 655
    • (2000) SPIE Med Imag , vol.3979 , pp. 646-655
    • Siadat, M.1    Soltanian-Zadeh, H.2
  • 30
    • 0031987381 scopus 로고    scopus 로고
    • Partial-volume Bayesian classification of material mixtures in MR volume data using voxel histograms
    • DH Laidlaw KW Fleisher AH Barr 1998 Partial-volume Bayesian classification of material mixtures in MR volume data using voxel histograms IEEE Trans Med Imag 17 74 86
    • (1998) IEEE Trans Med Imag , vol.17 , pp. 74-86
    • Laidlaw, D.H.1    Fleisher, K.W.2    Barr, A.H.3
  • 31
    • 0027646834 scopus 로고
    • Optimal transformation for correcting partial volume averaging effects in magnetic resonance imaging
    • H Soltanian-Zadeh J Windham A Yagle 1993 Optimal transformation for correcting partial volume averaging effects in magnetic resonance imaging IEEE Trans Nucl Sci 40 1204 1212
    • (1993) IEEE Trans Nucl Sci , vol.40 , pp. 1204-1212
    • Soltanian-Zadeh, H.1    Windham, J.2    Yagle, A.3
  • 32
    • 0023177446 scopus 로고
    • The contrast-to-noise in relaxation time, synthetic, and weighted-sum MR images
    • JN Lee SJ Riederer 1987 The contrast-to-noise in relaxation time, synthetic, and weighted-sum MR images Magn Reson Med 5 13 22
    • (1987) Magn Reson Med , vol.5 , pp. 13-22
    • Lee, J.N.1    Riederer, S.J.2
  • 33
  • 34
    • 0025972048 scopus 로고
    • Target-point combination of MR images
    • RB Buxton F Greensite 1991 Target-point combination of MR images Magn Reson Med 18 102 115
    • (1991) Magn Reson Med , vol.18 , pp. 102-115
    • Buxton, R.B.1    Greensite, F.2
  • 35
    • 0035185151 scopus 로고    scopus 로고
    • Feature space analysis: Effects of MRI protocols
    • H Soltanian-Zadeh D Peck 2001 Feature space analysis: Effects of MRI protocols Med Phys 28 2344 2351
    • (2001) Med Phys , vol.28 , pp. 2344-2351
    • Soltanian-Zadeh, H.1    Peck, D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.